This proposed work introduces an advanced system for detecting driver drowsiness, a key factor in global road accidents. The system uses Python and Opencv for strong image processing and includes a built-in system with a Wi-Fi-enabled NodeMCU and a vibration motor for real-time monitoring and immediate driver feedback. The approach begins with collecting a dataset containing images and videos of drivers in various states of alertness. These data are then pre-processed to emphasize features important for detecting drowsiness. Real-time video processing is achieved through Opencv, enabling the application of a trained model to live video streams for instant drowsiness detection. When drowsiness is detected, the system activates an alert using the NodeMCU to trigger a vibration motor, immediately warning the driver. The system’s effectiveness has been rigorously tested in both simulated and real-world scenarios, showing significant potential in enhancing road safety by reducing the risks associated with driver drowsiness.